This paper presents a total variation(TV) image denoising algorithm based on graph cut.
本文提出一种基于图割的全变差（TV）图像去噪算法。
The graph cut algorithm is one of high effective optimal methods in the stereo images matching.
图割算法是图像立体匹配算法中一种高效的最优化计算方法。
Two algorithms, graph cut and random walk based on graph theory, were applied to motion segmentation.
将两种基于图论的算法图切割与随机游走应用于运动对象的分割。
In this paper, for resolving these two problems, a new image Mosaic method based on graph cut is presented.
为解决这两个问题，提出了一种基于图切割的图像拼接方法。
Results show that for a single object, a clean and smooth segmentation can be quickly achieved by the graph cut.
结果表明：基于图切割算法可针对单目标快速、有效地进行分割，并获得干净、光滑的分割结果；
A new weight calculation method based on the statistics of gradient direction histogram is presented here in order to robustly realize graph cut.
本文给出新的基于梯度方向直方图统计的权值计算方法，实现稳定的图切割。
Aiming at the problem of poor real-time ability of graph cut, this paper suggests a remote sensing image segmentation approach based on quarter-tree and graph cut.
针对图割算法实时性差的问题，提出一种基于四叉树与图割的遥感图像分割方法。
To improve the efficiency of graph cut algorithm and reduce user interaction, the graph cut and mean shift algorithm were combined to automatically segment 3D vertebra images.
为提高图割算法的效率并减少用户交互量，提出将图割与均值漂移算法结合应用的脊椎骨自动分割方法。
Graph cut method is based on the theory of graphics, and it is one of hot spots in international image segmentation field recent years.
图切分方法是一种基于图论的分割方法，也是近年来国际图像分割领域的一个研究热点。
Moreover, to improve the disparity accuracy, a novel energy function is well designed to restrict the depth-continuity of an image and applied to the Graph Cut algorithm to describe the image feature.
并针对图像的深度连续性约束，定义了一个反映图像自身特征的新能量函数，应用于图割算法，提高了视差计算精度。
This thesis introduces and illustrates a general framework to integrate the areas of image segmentation and graph-cut theory.
本文介绍和阐述了整合图像分割和图割理论的基本框架。
The progressive segmentation algorithm can be seamlessly combined with multi-scale banded graph-cut optimizations to reduce the computational complexities in the banded optimizations.
渐进式分割算法可与多尺度图窄带分割算法无缝地结合，降低了对窄带进行优化的计算复杂度。
The progressive segmentation algorithm can be seamlessly combined with multi-scale banded graph-cut optimizations to reduce the computational complexities in the banded optimizations.
渐进式分割算法可与多尺度图窄带分割算法无缝地结合，降低了对窄带进行优化的计算复杂度。
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